icra planetary rover workshop / 19 may 2008 / d. thompson / carnegie mellon university a tale of two...

ICRA Planetary Rover Workshop / 19 May 2008 / D. Thompson / Carnegie Mellon University

A Tale of Two Rovers: Mission Scenarios for Kilometer-Scale Site Survey

David Thompson and David WettergreenThe Field Robotics Center, Carnegie Mellon


Agenda

Scarab: Surveying lunar regolith in polar craters Mission scenario

Mobility

Navigation and localization

Zoë: Intelligent surficial mapping Feature detection and classification

Kilometer-scale adaptive site survey

Conclusions


Technologies for site surveyT

err

ain

Diff

icu

lty

Autonomous Traverse Distance

AutonomousData

Collection

DarkNavigation

Slope and Crater Mobility

RobustLocalization Science

Autonomy

Integrationwith Orbital

Data


Scarab: lunar mission scenario

Land in crater

Supervised autonomy (polar orbiter relay)

Site Survey of regolith composition, hydrogen content

7 months, 25 drill sites over 25 kilometers


Mobility requirements

Challenging terrain

extreme slopes loose soil

Navigation and localization in lunar-analog environments

5.0cm/s dark navigation


A stable science / drilling platform

270kg mass 250 kg to counter drill

thrust

low CG

high torque

100kg Science payload

1m coring drill

Dark Navigation Sensors

RadioisotopeGenerator Simulator

Avionics

Science Payload

Regolith Drill Core System

Body Raise/Lower

Linkage & Actuator

Hazard Avoidance Sensors

“Differencing” Linkage


Suspension

Skid steering

Passive terrain matching / body averaging

Actuated rocker arms permit leveling / drilling on slopes

Kneels during drilling operations

improve stability

maximize drilling depth / minimize wasted travel


Auto-leveling


Inchworming

Inchworm: lower cycle

compaction resistance

tractive force

Inchworm: raise cycle

Conventional rolling

Theoretical benefitsmax slope: 19 vs. 23 degreesdrawbar pull: 1038 vs 1281N


Inchworming


Navigation

Dark navigation with active sensing

Laser light striping

Laser scan merging (courtesy NASA ARC)

Traversability analysis, D* path planning


NEPTEC TriDAR

Raster resolution to 512x512

30-degree FOV

accurate geologic maps for drill site selection


Localization

Wheel odometery is unreliable

Kalman-filtered IMU 3-axis ring laser gyro

3-axis acceleration

Optical velocity sensor with ground lighting


Field Tests

10h 50m, 1090m (2.8cm/s)

June – Mobility and autonomy testing at Moses lake WA

November – Science payload tests in Hawaii


Agenda

Scarab: Surveying lunar regolith in polar craters Mission scenario

Mobility

Navigation and localization

Zoë: Intelligent surficial mapping Feature detection and classification

Kilometer-scale adaptive site survey

Conclusions


Zoë: Surficial Survey Mission

Multiple-kilometer autonomous traverses

1m/s continuous travel in open terrain

Autonomous science feature recognition, data collection, and mapping

Tests at Amboy Crater, Mojave desert, CA

image courtesy Dom Jonak, CMU


Autonomous VISNIR acquisition

Automatic rock detection

Wide-baseline stereo estimates rock position

Autonomous spectrum classification

wavelength (nm)

0.0

1.0

0.8

0.6

0.4

0.2

850 1350 1850 2350350re

flect

an

cebasalt

sediment


MVJ detector for variable lighting

cascade 1

input image

max

h1

h2

hn...

nonrock

h1

h2

hn...

nonrock

cascade 2

h1

h2

hn...

nonrock

cascade m

.

.

.

rock bounding boxes

candidate bounding boxes


Rock detection and visual servo

SIFT matching recognizes and tracks dozens of targets

Science-relevant maps

Permits visual servo


Spectrum acquisition


Tracking performance

50

30

40

20

10

LostTrack

RockSpectra

Miss

MissMiss

Miss

RockSpectra Rock

SpectraRock

Spectra

LostTrack

LostTrack

LostTrack

Detection and tracking: 21 ( 3.9) rock spectra in 40 min

Blind pointing: 0 rock spectra


Rock detection

10m

N

rocks

final rover position

run 1

run 2

run 3 3.0

2.0

1.0

0.0

run 4

Rock Detection Precision: 90.8% (±2.6, =0.05)


Adaptive surficial mapping


Adaptive surficial mapping

“Gaussian process” terrain model

Site survey informed by surface and orbital data

Maximum-entropy sampling chooses optimal observation sites

Spatial inference

?

Cross-sensor inference

?


Inference Result 450m autonomous traverse

Extrapolates by interpreting orbital images

Discovers map parameters on the fly


Informative path planning

Science-driven

Adds robustness to execution uncertainty


Recovery from Navigation Error


Previously reported at iSAIRAS 2008 – Thompson, Wettergreen

Fidelity of Reconstructed Maps

Fixed, transect: 74% (±0.09) Fixed, coverage pattern: 75% (±0.05) Adaptive, low-res orbital: 81% (±0.03) Adaptive, high-res orbital: 87% (±0.01)

0.9

0.8

0.7

0.6

0.5

0 50 100 150 200 250 300number of returned features

reco

nstr

uctio

n ac

cura

cy


Conclusions

Mobility improvements facilitate new operational modes involving kilometer-scale site survey

Future work Selective data return (image

analysis and spatial statistics)

Data fusion for science and navigation (DEMs, orbital and surface images)


Thanks!

Field Robotics Center: David Wettergreen, Red Whittaker, David Kohanbash, Paul Bartlett, Dom Jonak, Jason Zigler

Johnson, Glenn, NORCAT, ARC

Scarab: NASA Human-Robot Systems research program, grants NNX08-AJ99G (Robert Ambrose) and NNX07-AE30G (John Caruso).

Zoë: NASA ASTEP NNG0-4GB66G (David Lavery)

icra planetary rover workshop / 19 may 2008 / d. thompson / carnegie mellon university a tale of two...

Documents

leveling drilling

drilling depth

lunar regolith

drill sites

lunar mission scenarioland

lunaranalog environments5

boxesrock detection

nonrock cascade 2h1h2hn